CBIL Doctoral Students


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Abhishek Singh Sambyal

His research interests lie in deep learning and medical image analysis. Specifically, he is working on problems related to the uncertainty quantification/calibration in deep neural networks for medical imaging applications. Prior to IIT Ropar, he completed his M. Tech. from Bangalore Institute of Technology. He spent two years at Kudos Knowledge as a Software Engineer in Bangalore and as an Assistant Professor at Central University of Jammu.

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Amanpreet Chander

Amanpreet completed his B.Tech in Electronics and Communication from UIET, Panjab University, Chandigarh. He has experience in embedded systems, circuit designing, virtual reality, 3D design, 3D printing, AI/ML and programming. He has executed multiple projects including a low-cost ambu-based ventilator, a smart pill dispensing device, and a smart oxygen-saving device called AMLEX. Currently, he is pursuing his Ph.D from IIT ropar and his research area is the development of affordable deep learning-based home rehabilitation systems for patients undergoing rehabilitation via physiotherapy.

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Ranjana Roy Chowdhury

Ranjana earned her B.Tech degree in CSE from Assam University Silchar and M.Tech degree in Services Computing from CSE Department, IIIT Guwahati. Her research areas focus on Few Shot Learning for Medical Image Analysis. Currently, she is working towards exploring various applications of Meta Learning Approaches towards solving few shot learning problems in the medical imaging domain.

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Usma Niyaz

Usma completed her undergraduate studies with a B.Tech. in Computer Science and Engineering from the University of Kashmir, followed by earning a Master's degree in Computer Science and Information Technology from the Central University of Jammu. She has worked as an assistant professor at the National Institute of Technology Srinagar, J&K, India. Her interest lies in addressing deep learning challenges within the field of medical imaging. Her current research focuses on model compression, a critical aspect of optimizing computational resources while ensuring the effectiveness of models in various medical imaging applications.

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Swati Kochhar

Swati is currently pursuing her doctoral degree in the Computer Science and Engineering department at the Indian Institute of Technology (IIT), Ropar. Her academic journey began with a B.Sc. in Information Technology, followed by an M.Sc. in Computer Science from Kumaun University, Uttarakhand. Her keen interest lies in the intersection of artificial intelligence, particularly reinforcement learning, and its applications in the medical domain. She is exploring the transformative potential of reinforcement learning in reshaping medical decision-making processes.

Alumni


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Anoop J. Thomas

Anoop is currently working on reducing the inter-scanner variability in activation in multicenter fMRI data. Before joining as a PhD student here at IIT Ropar, he worked as a Research Assistant in the Python group of FOSSEE at IIT Bombay where he was involved in the development of course content material, conducting workshops/conferences on Python. He completed my B.Tech from the University of Kerala, and worked as a lecturer for an year before joining FOSSEE.

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Apoorva Sikka

Apoorva graduated from GWECA Ajmer with a B.Tech. in Computer Engineerintg. She pursued her Masters from Malviya National Institute of Technology Jaipur in Computer Engineering. Her interests are in Computational Neuroimaging, applications of machine leaning to neuroimaging. Her current work focuses on the identifying Imaging Biomarkers that will help in detecting people who are at a risk of developing Alzheimer’s Disease using various machine learning techniques.

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Tara Chand

Tara Chand earned his B.Tech and M.Tech degrees in Cognitive Neuroscience from the Centre for Converging Technologies, University of Rajasthan, Jaipur. His research areas focus on the functional connectivity of the brain. currently, he is working towards exploring the application of different time series similarity metrics on fMRI data to capture both linear and nonlinear trends. He is currently pursuing his PhD at University of Tuebingen, Germany.